Hyperparameters are parameters that are set before the training of an AI model. They control the behaviour and performance of the model, such as learning rate, batch size, and regularisation strength. Selecting appropriate Hyperparameters is crucial for optimising model performance and improving accuracy.
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…